# tf.math.reduce_std

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 2 version](https://www.tensorflow.org/api_docs/python/tf/math/reduce_std) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/math_ops.py#L1921-L1964) |

Computes the standard deviation of elements across dimensions of a tensor.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.math.reduce_std`](https://www.tensorflow.org/api_docs/python/tf/math/reduce_std), \`tf.compat.v2.math.reduce_std\`

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    tf.math.reduce_std(
        input_tensor, axis=None, keepdims=False, name=None
    )

Reduces `input_tensor` along the dimensions given in `axis`.
Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each
entry in `axis`. If `keepdims` is true, the reduced dimensions
are retained with length 1.

If `axis` is None, all dimensions are reduced, and a
tensor with a single element is returned.

#### For example:

    x = tf.constant([[1., 2.], [3., 4.]])
    tf.reduce_std(x)  # 1.1180339887498949
    tf.reduce_std(x, 0)  # [1., 1.]
    tf.reduce_std(x, 1)  # [0.5,  0.5]

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| ## Args ||
|---|---|
| `input_tensor` | The tensor to reduce. Should have numeric type. |
| `axis` | The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(input_tensor), rank(input_tensor))`. |
| `keepdims` | If true, retains reduced dimensions with length 1. |
| `name` | A name scope for the associated operations (optional). |

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| ## Returns ||
|---|---|
| The reduced tensor, of the same dtype as the input_tensor. ||

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#### Numpy Compatibility

Equivalent to np.std

Please note that `np.std` has a `dtype` parameter that could be used to
specify the output type. By default this is `dtype=float64`. On the other
hand, `tf.reduce_std` has an aggressive type inference from `input_tensor`,